Defect Detection in Pharma Pills Using Image Processing

  • Abstract
  • Keywords
  • References
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  • Abstract

    In this work, methods for finding defects in pharma pills are proposed. Here pills are classified as tablets and capsules, further tablets are classified based on their shapes as oval shaped and round shaped tablets. Capsules are classified based on their colors in this three colors are considered that is red, green and blue double colored capsules like white-blue and white-brown are considered. While packing there may be some visible defects in the pills. This will vary the dosage of pills, manual inspection would be too tedious and less accurate so here some methods to identify these defects are proposed. Defects such as variation in count of tablets, cracks, breaks or variations in the size and shapes of tablets are considered. In capsules absence of capsule, variation in the size and shape of the capsules or presence of any other colored capsules are considered. These methods successfully detect number of non-defected tablets and number of defected tablets, and hence the non-defected tablets can be reused and defected tablets can be discarded.



  • Keywords

    Capsules; Defect; Image processing; Pharma pills; Tablets.

  • References

      [1] Munish Kumar Dhiman and Dr Rajat Gupta “Detection of Broken Blister using Canny and Rc-algorithm” International Journal of Scientific Research Engineering & Technology, Vol.3, Issue 3, June 2014.

      [2] Deepti and Rajiv Bansa, “Enhanced Feature Extraction Technique for Detection of Pharmaceutical Drugs” International Journal of Engineering Research and General Science, Vol.3, Issue 3, May-June, 2015

      [3] Shilpa and Arun Bhatia,“Enhanced Center of Mass Technique for Detection of Missing & Broken Pharmaceutical Drugs”, IJIRST –International Journal for Innovative Research in Science & Technology, Vol.3, Issue 01, June 2016.

      [4] Huvaida Manzoora and Yogeshwer Singh R, “Edge Detection in Digital Image Using Statistical Method”, IOSR Journal of Electronics and Communication Engineering, Vol.9, PP 15-19, Issue 3, May - Jun. 2014.

      [5] Ramya. S, Suchitra. J and Nadesh R.K, “Detection of Broken Pharmaceutical Drugs using Enhanced Feature Extraction Technique‖”, International Journal of Engineering and Technology (IJET), Vol5, Issue 2, Apr-May 2013.

      [6] Durga karthil, Vijayarekha K and Saranya S, “Identification of various defects in pharmaceutical tablets using image processing techniques”, Asian journal of pharmaceutical and clinical research, Vol.10, Issue 11, july 2017.

      [7] N. Shobha Rani, Nithusha V. K and Roshna T. P, “Automatic Recognition And Verification Of Defective Tablet Blisters Using Entropy Based Filtering And Histogram Processing”, International Journal of Applied Engineering Research, Vol.10, Number 5 (2015) pp. 13155-13167.

      [8] Munish Kumar Dhiman, Dr Rajat Gupta, ―Detection of Broken Blister using Canny and Rc-algorithm‖ International Journal of Scientific Research Engineering & Technology (IJSRET), ISSN 2278 – 0882 Vol.3, Issue 3, June 2014.

      [9] Joze Derganc, Bostjan Likar, Rok Bernard, Dejan Tomozevic, franjo Pernus, “Real-time automated visual inspection of color tablets in pharmaceutical blisters”, Journal of Real-Time Imaging, Vol.9 Issue 2, April 2003, Pages 113 – 124.

      [10] Hardeep Kaur, Er.Nidhi Garg, ―”Inspection of Defective Pharmaceutical Capsules using Harris Algorithm”, International Journal of Advances in Electronics Engineering, Vol:1 Issue:1 ISSN 2278 - 215X.

      [11] S. Akshay and P. Apoorva, "Segmentation and classification of FMM compressed retinal images using watershed and canny segmentation and support vector machine," 2017 International Conference on Communication and Signal Processing (ICCSP), Chennai, 2017, pp. 1035-1039.
      doi: 10.1109/ICCSP.2017.8286531.




Article ID: 14497
DOI: 10.14419/ijet.v7i3.3.14497

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